{"id":"W6959278746","doi":"10.1016/j.envsci.2025.104089","title":"Opportunities to better integrate inland fish and fisheries in multilateral environmental agreements","year":2025,"lang":"en","type":"article","venue":"Environmental Science & Policy","topic":"Plant Pathogens and Resistance","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"U.S. Geological Survey; Eesti Teadusagentuur; Great Lakes Fishery Commission","keywords":"Convention on Biological Diversity; Convention; CITES; Biodiversity; Fish <Actinopterygii>; Fishing; Legitimacy; Ecosystem","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001636642,0.0001537165,0.0001336372,0.00006878309,0.0002754702,0.0001022547,0.0002769718,0.00004488995,0.0001423147],"category_scores_gemma":[0.00001052621,0.00007036746,0.00002755532,0.0002007052,0.0005389365,0.0002614493,0.0002862362,0.00008354587,0.00001608069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001663813,"about_ca_system_score_gemma":0.00001184538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004184898,"about_ca_topic_score_gemma":0.0005533316,"domain_scores_codex":[0.9987941,0.00002955026,0.000177643,0.0003776248,0.0002217546,0.0003993583],"domain_scores_gemma":[0.9997275,0.00002655874,0.00003435548,0.00006098317,0.000001163325,0.000149435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000182368,0.00006098488,0.2712954,0.000001848489,0.000002423202,0.00001366634,0.0002149454,0.00000165207,0.6583393,0.00002656965,0.000353058,0.06967201],"study_design_scores_gemma":[0.0001161024,0.00006036874,0.9580326,0.00002316666,0.00000210139,0.000004278122,0.0008390625,0.00002942827,0.005614521,0.00008187103,0.03504857,0.0001478964],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929432,0.00003794771,5.81609e-7,0.005026311,0.00005688854,0.0001744095,0.0002664718,0.00001092469,0.001483252],"genre_scores_gemma":[0.9928002,0.0001644997,0.00006670993,0.004542082,0.00004744731,0.00001730106,0.00003070193,7.599196e-7,0.002330329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6867373,"threshold_uncertainty_score":0.2869502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01335279017373894,"score_gpt":0.2094565108177829,"score_spread":0.196103720644044,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}